As known, there is a wide literature and a relevant number of technical solutions related to the automatic control of the flight of autonomous aircraft (UAV). As known, the chance that a person controls the flight of a wing airfoil, such as for example a kite, mainly derives from the evaluation of position and orientation of a wing airfoil in space by seeing it, which offers the set of perception data which allow modulating the manoeuvre of the traction cables. The automation of the manoeuvre of wing airfoils therefore takes aim at reproducing human sensibility when driving a kite.
Reference art and literature however do not show solutions or studies which deal with the automatic control of the flight of power wing airfoils, in particular realised as “power kite”. In fact, it is deemed that the problems involved in this relevant control are multiple and complex, such as to require the most suitable use of the most advanced control methodologies and algorithms. The flight of a power wing airfoil and its modelisation in fact deal with the use of multi-variable non-linear systems, with control specifications to be observed with relevant robustness requirements with respect to parametric variations and to dynamics which cannot be modelled with enough accuracy. Depending on such characteristics, the control system must also provide control calibration functionalities designed on the virtual prototype, using experimental measures on the real system, when realised. The problems posed to the control of real systems by approximations of system mathematical models used for designing the control, have always been taken care of by researchers in the field, from the major works of Nyquist and Bode. It is however only starting from the 70's-80's that a relevant development of results occurred, able to systematically and quantitatively deal with the effect of the uncertainty of models used for analysing and synthesizing the control systems, giving rise to the development of the “robust” control area. Since these methodologies can be used for solving the majority of real problems, it is necessary to enact suitable identification methods which operate on measures performed on the real system to be controlled, designated in reference literature as robust identification, control-oriented identification or set membership identification.
Currently, no systems and/or processes are known for automatically controlling the flight of power wing airfoils which operate in a predictive way, namely, depending on observation and forecasts of future flight conditions of the wing airfoils themselves, and which allow taking into account critical situations and errors due to prediction.